极大有序二分解

Dominik Dürrschnabel, Gerd Stumme
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引用次数: 1

摘要

给定形式上下文,序数因子是其关联关系的子集,该关联关系在概念格中形成链,即数据集的一部分对应于线性顺序。为了在正式环境中可视化数据,Ganter和Glodeanu提出了一个基于两个有序因素的双坐标图。为了使双标图有用,重要的是这些因素包含尽可能多的数据点,即它们覆盖了发生率关系的大部分。在这项工作中,我们研究了这种有序的二分解。首先,我们研究了省略有序二因子分解的形式上下文中两个因子的不相交性。然后,我们证明了判定给定大小的两因子分解的存在性是一个np完全问题,这使得计算最大因子分解的计算成本很高。最后,我们提供了算法Ord2Factor,它允许我们计算大型有序双因子分解。
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Maximal Ordinal Two-Factorizations
Given a formal context, an ordinal factor is a subset of its incidence relation that forms a chain in the concept lattice, i.e., a part of the dataset that corresponds to a linear order. To visualize the data in a formal context, Ganter and Glodeanu proposed a biplot based on two ordinal factors. For the biplot to be useful, it is important that these factors comprise as much data points as possible, i.e., that they cover a large part of the incidence relation. In this work, we investigate such ordinal two-factorizations. First, we investigate for formal contexts that omit ordinal two-factorizations the disjointness of the two factors. Then, we show that deciding on the existence of two-factorizations of a given size is an NP-complete problem which makes computing maximal factorizations computationally expensive. Finally, we provide the algorithm Ord2Factor that allows us to compute large ordinal two-factorizations.
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